the term “normalization” stands as a cornerstone principle, a systematic approach to structuring relational databases to reduce data redundancy and improve data integrity.
It’s a theoretical framework with profound practical implications, guiding database designers toward optimal database schemas that are efficient, flexible, and robust.
This article delves into the theory behind database normalization and explores its practical application, shedding light on its benefits, challenges, and the various normal forms.
At its core
normalization is the process of organizing accurate cleaned numbers list from frist database the columns and tables of a relational database to minimize data duplication. The driving force behind this is the elimination of anomalies that can arise from redundant data.
These anomalies typically fall into three categories: insertion anomalies (difficulty adding new data), update anomalies (inconsistencies when updating data), and deletion anomalies (unintended loss of data).
By adhering to normalization principles, these anomalies are mitigated, ensuring that data remains consistent and accurate.
The theoretical foundation of normalization was laid by Edgar F. Codd, the pioneer of the relational model. Codd introduced the concept of “normal forms,” a series of guidelines or rules that dictate the structure of a database.
Each normal form represents a progressively stricter set of rules
aiming to eliminate specific types of data part of conceptual or logical models dependencies and redundancies. While there are several normal forms, the most commonly encountered and practically relevant are the First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and Boyce-Codd Normal Form (BCNF).
First Normal Form (1NF) is the most basic level korean number of normalization. A table is in 1NF if all its attributes (columns) contain atomic, indivisible values.
This means there are no repeating groups or multi-valued attributes within a single row. For example, a column storing multiple phone numbers separated by commas would violate 1NF.
To achieve 1NF, such a column would need to be split into separate columns for each phone number. Or better yet, a separate table would be created to store phone numbers, linked to the main table via a foreign key.
Moving beyond 1NF, Second Normal Form (2NF) addresses the concept of partial dependencies. A table is in 2NF if it is in 1NF and all its non-key attributes are fully functionally dependent on the entire primary key.
In simpler terms, if a table has a composite primary key (composed of two or more columns).
No non-key attribute should depend only on a part of that primary key.
If such a partial dependency exists, the offending attributes are moved to a separate.
Table along with the part of the primary key they depend on.
This ensures that each non-key attribute provides a fact about the whole key, not just a part of it.